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CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 6 months ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
ICASSP
2010
IEEE
13 years 10 months ago
Empirical quantization for sparse sampling systems
We propose a quantization design technique (estimator) suitable for new compressed sensing sampling systems whose ultimate goal is classification or detection. The design is base...
Michael A. Lexa
ICCV
2011
IEEE
12 years 10 months ago
Dense Disparity Maps from Sparse Disparity Measurements
In this work we propose a method for estimating disparity maps from very few measurements. Based on the theory of Compressive Sensing, our algorithm accurately reconstructs dispar...
Simon Hawe, Martin Kleinsteuber, Klaus Diepold
NECO
2008
129views more  NECO 2008»
13 years 10 months ago
Sparse Coding via Thresholding and Local Competition in Neural Circuits
While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not understood. We desc...
Christopher J. Rozell, Don H. Johnson, Richard G. ...
IGARSS
2009
13 years 7 months ago
Unmixing Sparse Hyperspectral Mixtures
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...
Marian-Daniel Iordache, José M. Bioucas-Dia...